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Revista Med
Print version ISSN 0121-5256On-line version ISSN 1909-7700
Abstract
RODRIGUEZ, ALEJANDRA et al. COMPLEXITY OF THE EXPRESSION OF GENES ASSOCIATED WITH OBESITY IN HUMAN ADIPOSE TISSUE. Rev. Med [online]. 2018, vol.26, n.1, pp.14-25. ISSN 0121-5256.
Objective:
To analyze the complexity of gene expression in the adipose tissue of genes associated with obesity, by computer simulation with different bioinformatics tools.
Methods:
After conducting a PubMed literature search, 37 genes associated with obesity with a fold change greater than 1.5 were selected. An interaction network was cons tructed using the Cytoscape 3.2 program from the calculation of z-score values obtained from DNA microarray experiments of adipose tissue samples collected from obese and control people. Detailed information on the genomic characteristics of these genes was extracted from the UCSC and NCBI Genome Browser databases. Using multivariate analysis tools, a principal component analysis and a cluster analysis were carried out.
Results:
The constructed network showed that the genes with the greatest number of interactions were: 1) the nuclear respiratory factor (NRF1), 2) the activated channel of potassium activate by calcium alpha 1 (KCNMA1), and 3) the fatty acid synthase (FASN). Those with the higher expression values were: 1) vascular endothelial growth factor A (VEGFA), 2) alpha-ketoglutarate-dependent dioxygenase (FTO), and 3) neuronal growth regulator 1 (NEGR1). The IL6, BDNF and HLC proteins had the highest interaction values with IL6R, NRF1 and ACACB, respectively. The most important ontological categories were related to lipoprotein metabolic processes, the tricarboxylic acid cycle, the activation of the MAP kinases, and the JNK cascade.
Conclusions:
As a whole, the results obtained from differential overexpression of genes associated with lipid metabolism in the adipose tissue of obese people could be a criterion to discriminate this pathology at a diagnostic level.
Keywords : Obesity; Adipose tissue; Gene expression; DNA microarrays; Bioinformatics.